Files
pytorch/torch/_dynamo/variables/streams.py
Maggie Moss d795fb225a [RFC] Add pyrefly to lintrunner (#165179)
This will add pyrefly to lint runner as a warning only - and allow us to collect feedback about the tool before switching to pyrefly as the main type checker.

References the steps outlined here: : https://github.com/pytorch/pytorch/issues/163283:

test plan:
`lintrunner init`
`lintrunner`
confirm when pyrefly errors are present results look like: https://gist.github.com/maggiemoss/e6cb2d015dd1ded560ae1329098cf33f

Pull Request resolved: https://github.com/pytorch/pytorch/pull/165179
Approved by: https://github.com/ezyang
2025-10-16 20:07:09 +00:00

212 lines
7.0 KiB
Python

from typing import Any
import torch
from torch.fx import Proxy
from .. import graph_break_hints
from ..exc import TYPE_CHECKING, unimplemented_v2
from .base import VariableTracker
from .constant import ConstantVariable
if TYPE_CHECKING:
from torch._dynamo.symbolic_convert import InstructionTranslator
from ..codegen import PyCodegen
from torch._library.custom_ops import custom_op
Tensor = torch.Tensor
@custom_op("streams::fork", mutates_args=())
def fork_stream(
from_index: int,
from_device: torch.device,
to_index: int,
to_device: torch.device,
) -> None:
pass
@fork_stream.register_fake
def _(
from_index: int,
from_device: torch.device,
to_index: int,
to_device: torch.device,
) -> None:
pass
@custom_op("streams::join", mutates_args=())
def join_stream(
from_index: int,
from_device: torch.device,
to_index: int,
to_device: torch.device,
) -> None:
pass
@join_stream.register_fake
def _(
from_index: int,
from_device: torch.device,
to_index: int,
to_device: torch.device,
) -> None:
pass
class StreamVariable(VariableTracker):
def __init__(
self,
proxy: Proxy,
value: torch.Stream,
device: torch.device,
**kwargs: Any,
) -> None:
if proxy is not None and "example_value" in proxy.node.meta:
assert proxy.node.meta["example_value"] == value
assert value.device.type == device.type, (
"stream value is not equal to the passed device"
)
super().__init__(**kwargs)
self.proxy = proxy
self.value = value
# pyrefly: ignore # read-only
self.device = device
def python_type(self) -> type:
return torch.Stream
def call_method(
self,
tx: "InstructionTranslator",
name: str,
args: list[VariableTracker],
kwargs: dict[str, VariableTracker],
) -> "VariableTracker":
assert hasattr(self.value, name), f"no stream method found named {name}"
from ..utils import cmp_name_to_op_mapping, proxy_args_kwargs
from .builder import wrap_fx_proxy_cls
if name in ("wait_stream", "synchronize", "wait_event"):
tx.output.create_proxy(
"call_method", name, *proxy_args_kwargs([self] + args, kwargs)
)
return ConstantVariable(None)
elif name == "query":
return wrap_fx_proxy_cls(
target_cls=ConstantVariable,
tx=tx,
proxy=tx.output.create_proxy(
"call_method", name, *proxy_args_kwargs([self] + args, kwargs)
),
)
elif name == "record_event":
return wrap_fx_proxy_cls(
target_cls=EventVariable,
tx=tx,
proxy=tx.output.create_proxy(
"call_method", name, *proxy_args_kwargs([self] + args, kwargs)
),
)
elif name in cmp_name_to_op_mapping and len(args) == 1 and not kwargs:
from ..guards import GuardBuilder, install_guard
if self.source:
install_guard(self.source.make_guard(GuardBuilder.EQUALS_MATCH))
# NB : Checking for mutation is necessary because we compare
# constant values
other = args[0]
if not isinstance(other, StreamVariable):
return ConstantVariable.create(NotImplemented)
if other.source:
install_guard(self.source.make_guard(GuardBuilder.EQUALS_MATCH))
return ConstantVariable.create(
cmp_name_to_op_mapping[name](self.value, other.value) # type: ignore[arg-type]
)
return super().call_method(tx, name, args, kwargs)
def as_proxy(self) -> Proxy:
return self.proxy
def reconstruct(self, codegen: "PyCodegen") -> None:
# If we got here, this stream is fully subsumed by the graph - this means it is
# not an input or global
assert not self.source
# Since we just proved that - for other such structures, like lists and dicts, reconstruction
# is fine and sound according to dynamo principles of treating collectives. However,
# streams are special in that we want to preserve the identity of the stream as the same as in the graph
# Normally, we would do this via codegen for the proxy mapping to an output - we cannot do this yet, as we do not
# yet have a plan for how we want to handle the case where the stream is used as an input or an output. Pending
# design, to unblock current work, we lift the stream into a global and then codegen bytecode to load it from there.
prefix = f"_stream_{self.device}"
name = codegen.tx.output.install_global_by_id(prefix, self.value)
codegen.append_output(codegen.create_load_global(name, add=True))
class EventVariable(VariableTracker):
def __init__(self, proxy: Proxy, value: torch.Event, **kwargs: Any) -> None:
if proxy is not None and "example_value" in proxy.node.meta:
assert proxy.node.meta["example_value"] == value
super().__init__(**kwargs)
self.proxy = proxy
self.value = value
def call_method(
self,
tx: "InstructionTranslator",
name: str,
args: list[VariableTracker],
kwargs: dict[str, VariableTracker],
) -> VariableTracker:
from ..utils import proxy_args_kwargs
from .builder import wrap_fx_proxy_cls
if name in ("wait", "record", "synchronize"):
tx.output.create_proxy(
"call_method", name, *proxy_args_kwargs([self] + args, kwargs)
)
return ConstantVariable(None)
elif name == "query":
return wrap_fx_proxy_cls(
target_cls=ConstantVariable,
tx=tx,
proxy=tx.output.create_proxy(
"call_method", name, *proxy_args_kwargs([self] + args, kwargs)
),
)
else:
method_name = (
f"{type(self.value).__module__}.{type(self.value).__qualname__}.{name}"
)
unimplemented_v2(
gb_type="Unsupported event method",
context=str(name),
explanation=f"Dynamo doesn't support tracing the {method_name} method. "
f"We currently support wait, record, synchronize, and query.",
hints=[
*graph_break_hints.SUPPORTABLE,
],
)
def as_proxy(self) -> Proxy:
return self.proxy
def reconstruct(self, codegen: "PyCodegen") -> None:
# If we got here, this event is fully subsumed by the graph - this means it is
# not an input or global
assert not self.source
# Similar to stream handling, we lift the event into a global and then codegen bytecode to load it from there.
prefix = "_event"
name = codegen.tx.output.install_global_by_id(prefix, self.value)
codegen.append_output(codegen.create_load_global(name, add=True))